A systematic review of empirical methods for modelling sectoral carbon emissions in China

Huang, L; Kelly, S; Lv, K; Giurco, D

A systematic review of empirical methods for modelling sectoral carbon emissions in China

Huang, L Kelly, S

Lv, K Giurco, D

Permalink

Publication Type:: Journal Article
Citation:: Journal of Cleaner Production, 2019, 215 pp. 1382 - 1401
Issue Date:: 2019-04-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download ManuscriptAdobe PDF (1.29 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Huang, L	en_US
dc.contributor.author	Kelly, S https://orcid.org/0000-0002-8454-6144	en_US
dc.contributor.author	Lv, K	en_US
dc.contributor.author	Giurco, D https://orcid.org/0000-0002-1707-9531	en_US
dc.date.available	2021-04-01T18:01:31Z
dc.date.issued	2019-04-01	en_US
dc.identifier.citation	Journal of Cleaner Production, 2019, 215 pp. 1382 - 1401	en_US
dc.identifier.issn	0959-6526	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135563
dc.description.abstract	© 2019 Elsevier Ltd A number of empirical methods have been developed to study China's sectoral carbon emissions (CSCE). Measuring these emissions is important for climate change mitigation. While several articles have reviewed specific methods, few attempts conduct a systematic analysis of all the major research methods. In total 807 papers were published on CSCE research between 1997 and 2017. The primary source of literature for this analysis was taken from the Web of Science database. Based on a bibliometric analysis using knowledge mapping with the software CiteSpace, the review identified five common families of methods: 1) environmentally-extended input-output analysis (EE-IOA), 2) index decomposition analysis (IDA), 3) econometrics, 4) carbon emission control efficiency evaluation and 5) simulation. The research revealed the main trends in each family of methods and has visualized this research into ten research clusters. In addition, the paper provides a direct comparison of all methods. The research results can help scholars quickly identify and compare different methods for addressing specific research questions.	en_US
dc.relation.ispartof	Journal of Cleaner Production	en_US
dc.relation.isbasedon	10.1016/j.jclepro.2019.01.058	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.classification	Environmental Sciences	en_US
dc.title	A systematic review of empirical methods for modelling sectoral carbon emissions in China	en_US
dc.type	Journal Article
utslib.citation.volume	215	en_US
utslib.for	0907 Environmental Engineering	en_US
utslib.for	0910 Manufacturing Engineering	en_US
utslib.for	0915 Interdisciplinary Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Institute For Sustainable Futures
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - ISF - Institute for Sustainable Futures
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	215	en_US

Abstract:

© 2019 Elsevier Ltd A number of empirical methods have been developed to study China's sectoral carbon emissions (CSCE). Measuring these emissions is important for climate change mitigation. While several articles have reviewed specific methods, few attempts conduct a systematic analysis of all the major research methods. In total 807 papers were published on CSCE research between 1997 and 2017. The primary source of literature for this analysis was taken from the Web of Science database. Based on a bibliometric analysis using knowledge mapping with the software CiteSpace, the review identified five common families of methods: 1) environmentally-extended input-output analysis (EE-IOA), 2) index decomposition analysis (IDA), 3) econometrics, 4) carbon emission control efficiency evaluation and 5) simulation. The research revealed the main trends in each family of methods and has visualized this research into ten research clusters. In addition, the paper provides a direct comparison of all methods. The research results can help scholars quickly identify and compare different methods for addressing specific research questions.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/135563